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. 2024 Apr 3;39(1):46.
doi: 10.1007/s00384-024-04621-y.

A new clinical model for predicting lymph node metastasis in T1 colorectal cancer

Kai Wang #  1   2 , Hui He #  3   2 , Yanyun Lin  3   2 , Yanhong Zhang  3   2 , Junguo Chen  3   2   4 , Jiancong Hu  5   6 , Xiaosheng He  7   8   9
Affiliations

A new clinical model for predicting lymph node metastasis in T1 colorectal cancer

Kai Wang et al. Int J Colorectal Dis. .

Abstract

Purpose: Lymph node metastasis (LNM) is a crucial factor that determines the prognosis of T1 colorectal cancer (CRC) patients. We aimed to develop a practical prediction model for LNM in T1 CRC.

Methods: We conducted a retrospective analysis of data from 825 patients with T1 CRC who underwent radical resection at a single center in China. All enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3 using R software. Risk factors for LNM were identified through multivariate logistic regression analyses. Subsequently, a prediction model was developed using the selected variables.

Results: The lymph node metastasis (LNM) rate was 10.1% in the training cohort and 9.3% in the validation cohort. In the training set, risk factors for LNM in T1 CRC were identified, including depressed endoscopic gross appearance, sex, submucosal invasion combined with tumor grade (DSI-TG), lymphovascular invasion (LVI), and tumor budding. LVI emerged as the most potent predictor for LNM. The prediction model based on these factors exhibited good discrimination ability in the validation sets (AUC: 79.3%). Compared to current guidelines, the model could potentially reduce over-surgery by 48.9%. Interestingly, we observed that sex had a differential impact on LNM between early-onset and late-onset CRC patients.

Conclusions: We developed a clinical prediction model for LNM in T1 CRC using five factors that are easily accessible in clinical practice. The model has better predictive performance and practicality than the current guidelines and can assist clinicians in making treatment decisions for T1 CRC patients.

Keywords: Depth of submucosal invasion (DSI); Lymph node metastasis (LNM); Prediction; Sex; T1 colorectal cancer (CRC).

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Consort diagram of collected T1 colorectal cancers (CRCs). LN Lymph node, LNM lymph node metastasis
Fig. 2
Fig. 2
Performance evaluation of the prediction model in predicting lymph node metastasis from validation data set. A A receiver operating characteristic curve analysis to compare the performance of the risk factors of current guidelines, guideline-combination model and the prediction model in a validation cohort. B Comparison of overtreatment frequency among current guidelines, guideline-combination model and our prediction model. HR high risk, LR low risk, LNM lymph node metastasis
See this image and copyright information in PMC

References

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